📢 Gate Square #Creator Campaign Phase 2# is officially live!
Join the ZKWASM event series, share your insights, and win a share of 4,000 $ZKWASM!
As a pioneer in zk-based public chains, ZKWASM is now being prominently promoted on the Gate platform!
Three major campaigns are launching simultaneously: Launchpool subscription, CandyDrop airdrop, and Alpha exclusive trading — don’t miss out!
🎨 Campaign 1: Post on Gate Square and win content rewards
📅 Time: July 25, 22:00 – July 29, 22:00 (UTC+8)
📌 How to participate:
Post original content (at least 100 words) on Gate Square related to
MiniMax Open Source's first inference model: Competing with DeepSeek, the Computing Power cost is only about $530,000.
Gate News bot message, MiniMax announced on June 17 that it will release important updates for five consecutive days. Today's first release is the Open Source first inference model MiniMax-M1.
According to the official report, the MiniMax-M1 has benchmarked alongside open source models such as DeepSeek-R1 and Qwen3, approaching the most advanced models overseas.
The official blog also mentioned that based on two major technological innovations, the MiniMax-M1 training process was efficient "beyond expectations," completing the reinforcement learning training phase in just 3 weeks using 512 H800 GPUs, with a computing power rental cost of only $534,700. This is an order of magnitude less than the initial expectations.
Source: Jinshi